The American journal of emergency medicine
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Currently the videographic review of emergency intubations is an unstructured, qualitative process. We created a taxonomy of errors that impede the optimal procedural performance of emergency intubation. ⋯ We developed a taxonomy of 13 performance errors of laryngoscopy. Further study is warranted to determine how to best incorporate these into emergency airway training and the airway review process.
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Tumor lysis syndrome (TLS) is an acutely life threatening, must-not miss, oncological emergency that infrequently presents to the emergency department (ED). This diagnosis is typically a complication of chemotherapy, however, TLS can also occur spontaneously as the first presentation of malignancy. ⋯ Further workup revealed the diagnosis of pre-B cell acute lymphoblastic leukemia. This case emphasizes the consideration of TLS as a cause of acute renal failure or severe electrolyte derangements in those who may not have a known diagnosis of malignancy or recent chemotherapy.
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Randomized Controlled Trial Comparative Study
Dexmedetomidine versus propofol: An effective combination with ketamine for adult procedural sedation: A randomized clinical trial.
Recently, drug combination protocols have been preferred over single drugs in procedural sedation and analgesia (PSA). This study aimed to compare the effectiveness and hemodynamic profile of ketamine-dexmedetomidine (ketodex) and ketofol as drug combinations with ketamine as a single medication for PSA in the emergency department (ED). ⋯ Ketodex, as well as ketofol, were effective and safe combinations with good recovery profiles and hemodynamic stability for adult PSA in ED.
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The emergency department (ED) triage process serves as a crucial first step for patients seeking acute care, This initial assessment holds crucial implications for patient survival and prognosis. In this study, a systematic review of the existing literature was performed to investigate the performance of machine learning (ML) models in recognizing and predicting the need for intensive care among ED patients. ⋯ ML models have demonstrated good performance in identifying and predicting critically ill patients in ED triage. However, because of the limited number of studies on each model, further high-quality prospective research is needed to validate these findings.